TY - JOUR
T1 - In-store behavioral analytics technology selection using fuzzy decision making
AU - Dogan, Onur
AU - Öztaysi, Basar
N1 - Publisher Copyright:
© 2018, Emerald Publishing Limited.
PY - 2018/7/9
Y1 - 2018/7/9
N2 - Purpose: With the emerging technologies, collecting and processing data about the behaviors of customers or employees in a specific location has become possible. The purpose of this paper is to evaluate existing data collection technologies. Design/methodology/approach: Technology evaluation problem is handled as a multi-criteria decision-making (MCDM) problem. In this manner, a decision model containing four criteria and eight sub-criteria and four alternatives are formed. The problem is solved using hesitant analytic hierarchy process (AHP) and trapezoidal fuzzy numbers (TrFN). Findings: The results show that the most important sub-criteria are: accuracy, quantity, ıntrospective and cost. Decision makers’ evaluate for alternatives, namely wireless fidelity (WiFi), camera, radio-frequency identification and Bluetooth. The best alternative is found as Bluetooth which is followed by WiFi and Camera. Research limitations/implications: Technology evaluation problem, just like many other MCDM problems are solved using expert evaluations. Thus, the generalizability of the findings is low. Originality/value: In this paper, technology selection problem has been handled using hesitant AHP for the first time. In addition, the original methodology is extended by using TrFN to represent the expert evaluations in a better way.
AB - Purpose: With the emerging technologies, collecting and processing data about the behaviors of customers or employees in a specific location has become possible. The purpose of this paper is to evaluate existing data collection technologies. Design/methodology/approach: Technology evaluation problem is handled as a multi-criteria decision-making (MCDM) problem. In this manner, a decision model containing four criteria and eight sub-criteria and four alternatives are formed. The problem is solved using hesitant analytic hierarchy process (AHP) and trapezoidal fuzzy numbers (TrFN). Findings: The results show that the most important sub-criteria are: accuracy, quantity, ıntrospective and cost. Decision makers’ evaluate for alternatives, namely wireless fidelity (WiFi), camera, radio-frequency identification and Bluetooth. The best alternative is found as Bluetooth which is followed by WiFi and Camera. Research limitations/implications: Technology evaluation problem, just like many other MCDM problems are solved using expert evaluations. Thus, the generalizability of the findings is low. Originality/value: In this paper, technology selection problem has been handled using hesitant AHP for the first time. In addition, the original methodology is extended by using TrFN to represent the expert evaluations in a better way.
KW - Analytic hierarchy process
KW - Behavioural analytics
KW - Hesitant fuzzy sets
KW - Technology selection
UR - http://www.scopus.com/inward/record.url?scp=85049840423&partnerID=8YFLogxK
U2 - 10.1108/JEIM-02-2018-0035
DO - 10.1108/JEIM-02-2018-0035
M3 - Article
AN - SCOPUS:85049840423
SN - 1741-0398
VL - 31
SP - 612
EP - 630
JO - Journal of Enterprise Information Management
JF - Journal of Enterprise Information Management
IS - 4
ER -